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Model compression

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, 2006
Often the best performing supervised learning models are ensembles of hundreds or thousands of base-level classifiers. Unfortunately, the space required to store this many classifiers, and the time required to execute them at run-time, prohibits their use in applications where test sets are large (e.g. Google), where storage space is at a premium (e.g.
Cristian Buciluǎ   +2 more
openaire   +1 more source

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